SuperAPI AI Directory

gemini-3-image-prompt

Design & creation

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Updated 10-15 21:41

About this skill

Gemini 3 Pro Image Prompt Builder — 5-Component + 3-Model Simultaneous Output

moai-media | Image Prompt Builder (text output only)

Overview

Gemini 3 Pro Image (Nano Banana Pro) is Google DeepMind's reasoning-driven image generation and editing model, and Thinking Mode, Perfect Text Rendering, Search Grounding (Google Search integration), Few-Shot Design (up to 14 reference images) are supported. The natural language prompt tone works best when it is the tone of a Creative Director directing a scene.

This skill converts a user's one-line request into the 5-component structure from the official Google AI for Developers guide:

[Subject + Adjectives] doing [Action] in [Location/Context].
[Composition/Camera]. [Lighting/Atmosphere]. [Style/Media].
[Specific Constraint/Text]

Each component ends with an English sentence and is separated by a period. Keyword-list style works, but result quality is lower.

In particular, this skill:

  • 3-model simultaneous output: Gemini 5-component main + GPT-image-2 (6-Block) + Midjourney v8.1 (keywords + parameters)
  • Presets + fine-tuning: 4 presets (product shot, portrait, illustration, landscape) × 4 slots
  • Thinking vs Fast mode guidance: Thinking for complex composition and text, Fast for quick exploration (Gemini 3.1 Flash Image)
  • Camera hardware specification: Hardware instructions that determine visual DNA, such as GoPro, Fujifilm, disposable, iPhone, etc.

Paired skill higgsfield-image(Higgsfield MCP — 11 image models including Nano Banana Pro) generates the actual image, and this skill outputs only the prompt text .

Trigger keywords

Gemini image prompt Nano Banana prompt Nano Banana Pro prompt Gemini 3 Pro Image prompt Google AI Studio image Vertex AI image prompt SynthID

Workflow

사용자 자연어 한 줄
    ↓
[Round 1] AskUserQuestion — 프리셋 선택 (제품샷·인물·일러스트·풍경)
    ↓
[Round 2] AskUserQuestion — 프리셋별 미세조정 (3~4 슬롯)
    ↓
[Round 3] AskUserQuestion — 화면비 + 이미지 내 텍스트 유무 + 카메라 하드웨어(선택)
    ↓
[내부] 슬롯 → 5-component 매핑
    ↓
[내부] 같은 슬롯 → GPT 6-Block + MJ 키워드+파라미터 변환
    ↓
출력: 3개 모델 프롬프트 코드블록 + 권장 파라미터 + 한국어 해설

Execution rules

Round 1 — Preset selection (required)

AskUserQuestionis called to have the user select 1 of 4 presets.

Preset Applicable cases references
Product shot (recommended) Commerce products, package shots, jewelry and watch close-ups presets/product-shot.md
People and characters Portraits, personas, advertising models presets/portrait.md
Illustration and art Card news illustrations, book covers, concept art presets/illustration.md
Landscape and environment Background images, cinematic backgrounds, travel shots presets/landscape.md

Round 2 — Preset-specific fine-tuning (3-4 questions)

presets/<name>.mdFollows the slot definitions of . This skill's presets/ uses the same slot data as gpt-image-2-prompt, but the per-model tone conversion guide is automatically converted to the Gemini Creative Director tone.

Round 3 — Aspect ratio + text + camera hardware (optional)

Aspect ratio Gemini mapping Purpose
1:1 (recommended) aspect_ratio="1:1" SNS square, general
16:9 "16:9" Wide, YouTube
9:16 "9:16" Reels·Shorts
4:5 "4:5" Instagram feed
21:9 "21:9" Cinematic ultrawide (Gemini only)

Gemini additionally supports 3:2, 2:3, 3:4, 4:3, 5:4, and Gemini 3.1 Flash Image also supports 1:4, 4:1, 1:8, 8:1.

Camera hardware options (core of the Gemini Creative Director tone):

Option Visual DNA
Default (DSLR 50mm) Clean·neutral·standard
Fujifilm X-T5 Warm tones, film simulation tone
GoPro HERO12 Wide-angle, action·immersive, slight distortion
Disposable film camera Coarse grain, nostalgic flash, raw mood
iPhone 15 Pro Clean digital, computational photography

Internal processing — slot → 5-Component mapping

Component 1 — [Subject + Adjectives] doing [Action] in [Location]
Component 2 — [Composition/Camera Angle/Lens/Hardware]
Component 3 — [Lighting/Atmosphere]
Component 4 — [Style/Media]
Component 5 — [Specific Constraint/Text]

Each component is 1-2 English sentences. Separated by periods. For detailed rules, see references/prompt-blocks.md.

Internal processing — GPT 6-Block + MJ conversion

Same logic as the paired skills gpt-image-2-prompt / midjourney-v8-prompt.

Output — 3 model code blocks

## 🎨 생성된 프롬프트 (3개 모델)

### 1) Gemini 3 Pro Image — Nano Banana Pro (메인)

<5-component English sentences>

**권장 파라미터**: `aspect_ratio=1:1`, `resolution=2K`, `mode=Thinking`
**Reference 이미지**: 최대 14개 첨부 가능 (`references/reference-images.md`)
**Search Grounding**: 데이터 시각화·지도·통계 그래프는 활성화 권장

### 2) GPT-image-2 — OpenAI ChatGPT / API

<6-Block natural language paragraph>

**권장 파라미터**: `quality=medium`, `size=1024x1024`, `moderation=auto`

### 3) Midjourney v8.1

<keyword, keyword, ... --ar 1:1 --style raw --hd --q 4 --s 300>


### 📝 한국어 해설
- Gemini는 Creative Director 어조에 가장 잘 반응합니다 (chiaroscuro · golden hour backlighting · three-point softbox 등)
- Thinking Mode는 복잡 구도·텍스트·데이터 시각화에 유리, latency 증가
- 모든 출력 이미지에 SynthID 워터마크 자동 삽입 (imperceptible)

### 🔗 페어 스킬 (실제 이미지 생성)
- `higgsfield-image` — Higgsfield MCP 직접 호출 (Nano Banana Pro 포함, 실제 이미지 생성)
- `gpt-image-2-prompt` — GPT 어조 프롬프트 빌더 (sibling)
- `midjourney-v8-prompt` — MJ 어조 프롬프트 빌더 (sibling)

Text-First workflow

The 2-step pattern officially recommended by Google when the text to go into the image is long or complex:

  1. First, refine the text concept through conversation with the model ("recommend a short copy that fits this kind of mood").
  2. Then put the finalized text verbatim into the image prompt.

This skill automatically recommends using the Text-First pattern when the text length is 30 characters or more in Round 3.

Usage examples

Example 1: Product shot

"Gemini image prompt, product shot of a matte black mug with the word 'MONDAY'"

→ Round 1: product shot → Round 2: mug/slate/window/3-4 minutes → Round 3: 1:1 + verbatim "MONDAY" + Fujifilm → output Gemini main + GPT + MJ simultaneously.

Example 2: Infographic (Search Grounding)

"Infographic comparing the number of Korean SNS users in 2026 with a nano-banana prompt"

→ Select illustration preset → Round 2 slots → Search Grounding activation guidance + Thinking Mode recommended.

Example 3: Cinematic landscape 21:9

"Gemini 3 Pro Image cinematic landscape prompt, Han River sunset 21:9"

→ Landscape preset → Round 2 → 21:9 + GoPro wide → note that only Gemini supports 21:9.

Output format

Deliverable Format Description
Gemini 3 Pro Image prompt English 5-component paragraph Copy-paste into Google AI Studio / Vertex AI / Gemini app
GPT-image-2 prompt English 6-Block natural language paragraph Copy-paste into ChatGPT / API
Midjourney v8.1 prompt Keyword + --파라미터 Discord /imagine or alpha.midjourney.com
Recommended parameters aspect/quality/mode per model Enter together when configuring API/UI
Korean commentary Markdown Tone differences, Thinking mode, SynthID, cost cautions

Cautions

  • This skill prompt text only outputs. For actual image generation, use the paired skill.
  • All outputs from Gemini 3 Pro Image have an imperceptible SynthID watermark embedded (Google policy, cannot be changed).
  • Thinking Mode increases latency, but is essential when complex composition, multiple objects, data visualization, or accurate text is required.
  • Even when generating fact-based infographics with Search Grounding, results always require separate verification (the model may misinterpret information).
  • Input tokens: Gemini 3 Pro Image 65,536 tokens, Flash 131,072 tokens. Output tokens: 32,768 (both).
  • When attaching reference images, it is recommended to place core elements (style, character, composition) in the first 2-3, and use the rest as secondary style.
  • Masking edits, day-to-night conversion, and multi-image blending sometimes produce unnatural results or artifacts.

Related skills

Skill Relationship Description
gpt-image-2-prompt sibling GPT 6-Block tone prompt with the same input
midjourney-v8-prompt sibling MJ keyword+parameter prompt with the same input
higgsfield-image after Actual image generation via direct Higgsfield MCP call (including Nano Banana Pro)

Sources

Primary recommended sources (official):

Industry references:

Based on the above sources, we derived the 5-component structure, Thinking/Fast mode recommendations, aspect_ratio range, 14 reference images, SynthID policy, 65K/32K token limits, and Search Grounding utilization.